AI Technical Architect

Role - AI Technical Architect

Experience - 15+ years

Budget - Up to 55 LPA including 15% variables

Work Mode - Remote

Required Notice Period - Immediate to 30 days

Required Skills :

Extensive AI / ML Experience : Deep knowledge of artificial intelligence and machine learning concepts, particularly in natural language processing (NLP) and large language models (LLMs).

Software Architecture Expertise : Strong understanding of software architecture principles, including scalability, modularity, and security.

Cloud Computing Proficiency : Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and distributed computing environments.

Data Architecture Knowledge : Familiarity with data management practices, big data technologies, and data pipeline design.

MLOps Experience : Understanding of MLOps practices for continuous integration, delivery, and monitoring of machine learning models.

Leadership Skills : Strong leadership abilities to guide technical teams and communicate effectively with non-technical stakeholders.

Problem-Solving Abilities : Excellent analytical skills to address complex technical challenges and devise innovative solutions.

Key Responsibilities :

Design and Oversee AI Architecture : Develop the overall architecture for the LLM from pretraining to supervised fine tuning and RLHF.

Technical Strategy and Roadmap : Define the technical strategy and create a roadmap for the project, aligning it with organizational goals.

Technology Selection : Make high-level decisions on technology stack, frameworks, and tools to be used in the development and deployment of the use case, platforms and solutions.

Integration Management : Oversee the integration of various AI components, including data pipelines, model training environments, and deployment infrastructure.

Risk Management : Identify potential technical risks in the project and develop strategies to mitigate them.

Collaboration : Work closely with data scientists, engineers, domain experts, and stakeholders to ensure cohesive development and implementation.

Innovation and Best Practices : Stay informed about the latest advancements in AI technology and implement best practices to enhance the LLM's capabilities. Research and Evaluation : Conduct comprehensive research on existing LLM architectures, including open-source models like GPT, Mistral, DeepSeek, Qwwn, and domain-specific variants like FinBERT.

To apply, connect with Abhishek via abhishek.m@livecjobs.com or WhatsApp on 9154908075